Needs to be done in exactly 24 hours, Using Jupyter (Python) budget is 40$
The dataset [login to view URL] contains information on 1302 American colleges and universities offering an undergraduate program. For each university, there are 17 measurements that include continuous measurements (such as tuition and graduation rate) and categorical measurements (such as location by state and whether it is a private or a public school).
1. Remove all categorical variables.
2. Remove all records with missing numerical measurements from the dataset.
3. Conduct a principal components analysis on the cleaned data and comment on the results.
4- Should the data be normalized?
5- Discuss which components are key to your analysis.
Bu iş için 5 freelancer ortalamada $52 teklif veriyor
Hey there, Wish you the best. I have read your project description and I will be happy to help you with it. I'm familiar with industrial engineering and also a data scientist and the statistical analysis and clustering Daha Fazla
I can use pandas and python3 in jupyter notebook , for the give requirements, you can share more details of the work in chat
Hi, I have very good skills in python programming, of course I am familiar with jupyter notebook. I will deliver results in 24 hours, promise I hope to do this project for you. Thanks
Hello! I have analyzed the dataset . As per the need , I am available full time on this platform and this work would not consume much time . Will hand it over in minimum time within 24 hrs. Thanx